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Auto-enable tf2onnx large_model for models >1.5GB (#22825) #6

Auto-enable tf2onnx large_model for models >1.5GB (#22825)

Auto-enable tf2onnx large_model for models >1.5GB (#22825) #6

Workflow file for this run

name: Keras GPU Tests
on:
push:
branches: [master]
pull_request:
types: [unlabeled]
release:
types: [created]
permissions:
contents: read
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
jobs:
test-in-container:
# Only run on pushes to master, releases or "kokoro:force-run" unlabel
if: |
github.event_name == 'push' ||
github.event_name == 'release' ||
(github.event.action == 'unlabeled' && github.event.label.name == 'kokoro:force-run')
strategy:
fail-fast: false
matrix:
backend: [jax, tensorflow, torch]
name: Run tests on GPU
runs-on: linux-x86-g2-16-l4-1gpu
timeout-minutes: 120
container:
image: python:3.11-slim
options: --privileged --network host
env:
KERAS_HOME: .github/workflows/config/${{ matrix.backend }}
steps:
- name: Checkout ${{ github.ref }}
uses: actions/checkout@v6
- name: Check CUDA Version
run: nvidia-smi
- name: Install binary dependencies
# build-essential is the C++ compiler for Torch Dynamo
# curl, git, gpg are for codecov/codecov-action
run: |
apt-get update
apt-get -y install build-essential
apt-get -y install curl
apt-get -y install git
apt-get -y install gnupg
- name: Install Python dependencies
run: pip install --no-cache-dir -r requirements-${{ matrix.backend }}-cuda.txt
- name: Verify TF Installation
if: ${{ matrix.backend == 'tensorflow'}}
run: python3 -c "import tensorflow as tf; print('Tensorflow devices:', tf.config.list_logical_devices()); assert len(tf.config.list_physical_devices('GPU')) > 0"
- name: Verify JAX Installation
if: ${{ matrix.backend == 'jax'}}
run: python3 -c "import jax; print('JAX devices:', jax.devices(), jax.devices()[0].device_kind); assert jax.default_backend() == 'gpu'"
- name: Verify Torch Installation
if: ${{ matrix.backend == 'torch'}}
run: python3 -c "import torch; print('Torch devices:', [torch.cuda.get_device_name(i) for i in range(torch.cuda.device_count())]); assert torch.cuda.device_count() > 0"
- name: Run Tests
run: pytest keras --ignore keras/src/applications --cov=keras --cov-config=pyproject.toml
- name: Convert Coverage
run: coverage xml --omit='keras/src/applications/*,keras/api' -o core-coverage.xml
- name: Upload Coverage
uses: codecov/codecov-action@57e3a136b779b570ffcdbf80b3bdc90e7fab3de2 # v5
with:
env_vars: KERAS_HOME
flags: keras,keras-gpu,keras-${{ matrix.backend }}
files: core-coverage.xml
token: ${{ secrets.CODECOV_TOKEN }}
fail_ci_if_error: false